Making Your Geospatial Data Workflow Simpler with Galileo Collections

If you’ve ever spent hours sifting through geospatial layers, only to lose track of what you found or where you found it, you’re not alone. It’s a challenge I’ve faced myself and something I’ve heard time and again from others in the geospatial community. We’re often bouncing between various geoportals, databases, and search engines, trying to piece together the data we need for our projects. It’s like putting together a jigsaw puzzle without knowing if you have all the pieces.

That’s why I’m particularly excited to share with you a new feature in Galileo that I think will genuinely make our lives easier: Collections

The Problem We All Know Too Well

For those of us who work with geospatial data, organization can be a major pain point. Imagine this: You’ve spent hours combing through datasets, finally found a few layers that seem perfect for your project, but when you return to them later, you can’t remember where you found them or how they fit together. It’s frustrating, time consuming, and frankly, a bit demoralizing.

I’ve often wished for a simple way to keep track of the layers I’ve discovered, something that lets me come back to them later without starting my search from scratch. And even better, something that would let me share these findings with my team, so we’re all on the same page, literally.

Enter Galileo Collections

With the new Collections feature in Galileo, we’ve tried to solve these exact problems. Now, when you find a layer in our search engine, you can save it to a collection, a sort of personalized folder where you can gather and organize the layers you’ve found.

Think of it as a way to bookmark your most valuable data, but better. Not only can you return to your collection whenever you want, but you can also add notes, organize layers by themes or projects, and even share your collections with colleagues.

How It Works

Using Collections is straightforward. As you browse through datasets on Galileo, you’ll now see an option to “Add to Collection.” With a few clicks, that layer is saved to a collection of your choosing. You can create multiple collections for different projects, themes, or whatever organizational system works best for you.

When you’re ready to dive back into a project, your collection is there, waiting for you, with all your layers neatly organized and ready to go. No more retracing your steps, no more wasted time, and no more frustration.

Want to see an example? Check out this collection I created of Florida Panther Datasets!

Why It Matters

I genuinely believe that this feature is going to make a difference for those of us who rely on geospatial data in our work. It’s about making the workflow smoother and more intuitive, reducing the friction that often comes with managing large amounts of data. And it’s about giving you back control over your data discovery process.

Instead of feeling like you’re constantly reinventing the wheel with each project, Collections allows you to build a library of resources that you can return to time and again. And because you can share these collections, it’s a powerful tool for collaboration. Whether you’re working with a team or just want to show a colleague what you’ve found, sharing a collection is as simple as sending a link.

A Step Toward Simplicity

At the end of the day, our goal with Galileo is to make your work easier, more efficient, and more enjoyable. We know that the tools you use can make a huge difference in how you approach your work, and we want Galileo to be a tool that you genuinely enjoy using.

The Collections feature is a step in that direction, a small but meaningful way to simplify your workflow, help you stay organized, and save you time. I hope you find it as useful as I do, and I can’t wait to see how you use it to make your work even better.

If you haven’t tried it out yet, I encourage you to give it a go and see how it can fit into your workflow. And as always, I’d love to hear your feedback, what’s working, what could be better, and what you’d like to see next.